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updated tests/german/object-order.README

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Hans Leiss
2019-07-04 10:19:24 +02:00
parent b521089274
commit 07aa656687
1 changed files with 26 additions and 13 deletions
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tests/german/object-order.README
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@@ -87,7 +87,7 @@ contained in examples.txt. (Definiteness seems to be relevant to order, too.)
ich trinke warmes Bier nicht [ ich trinke nicht Bier: via no_Predet ]
The order accPron < refl < (gen|dat)Pron < neg < nonpronNP sometimes sounds
better, but expresses a different meaning (often available via no_Preded):
better, but expresses a different meaning (often available via no_Predet):
sie hat sich nicht alle|viele|?mehrere Namen gemerkt
sie hat sich alle?|viele|mehrere Namen nicht gemerkt
@@ -98,7 +98,10 @@ contained in examples.txt. (Definiteness seems to be relevant to order, too.)
einige Lehrer haben jedem Studenten viele Bücher nicht geschickt|empfohlen
=?= some teachers haven't sent|recommended many books to every student
For tests, see examples.txt and TestLangGer.
For tests, see examples.txt and how to do regression tests (see below).
Rem.: Having more nn-fields may be useful to put adverbs in between (with
additional scope problems).
4. For reflexive V2's (ich bediene mich einer Sache, ich merke mir eine Sache) or
reflexive V3's (ich entschuldige mich bei dat für acc, ich leihe mir acc bei dat),
@@ -236,16 +239,14 @@ Also, singular mass-NPs behave different:
ich trinke nicht *((kaltes) Bier)
ich trinke (kaltes) Bier nicht | ich trinke kein (kaltes) Bier
PROBLEMS: do V2 + neg behave the same as V3 + neg? Can the scope of negation
and quantifiers be fixed (or at least restricted) by intonation?
PROBLEM: do V2 + neg behave the same as V3 + neg? Aren't the relative
scopes of negation and quantifiers fixed (or restricted) by intonation?
------------- Generating some example trees and linearize them (LangGer|Eng) -----------
gr -tr -number=4 UseCl (TTAnt ? ?) ? (PredVP (UsePron i_Pron) (ComplSlash (SlashVV want_VV (SlashV2a see_V2)) (DetCN (DetQuant ? ?) (UseN man_N)))) | l
gr -number=4 -tr UseCl (TTAnt ? ?) ? (PredVP (UsePron i_Pron) (ComplSlash (SlashVV want_VV (SlashV2a see_V2)) (DetCN (DetQuantOrd ? ? ?) (UseN man_N)))) | l
Pronoun switch with V3 and Slash3V2 works:
Pronoun switch with V3 and Slash?V2 works:
l UseCl (TTAnt TPast AAnter) PPos (PredVP (UsePron i_Pron) (ComplSlash (Slash3V3 sell_V3 (DetCN (DetQuant IndefArt NumSg) (UseN woman_N))) (DetCN (DetQuant DefArt NumSg) (UseN book_N))))
I had sold the book to a woman
@@ -255,14 +256,26 @@ l UseCl (TTAnt TCond ASimul) PNeg (PredVP (UsePron i_Pron) (ComplSlash (Slash3V3
I wouldn't sell it to her
ich würde es ihr nicht verkaufen
--------------------- Regression tests -----------------------------------
------ Regression tests: use gf --run < object-order.gfs or gf> eh object-order.gfs
From Eng to Ger:
Lang> rf -file=examples.eng.txt -lines | p -lang=LangEng | l -lang="LangEng,LangGer" -treebank | wf -file=examples.eng.new
Lang> rf -file=examples.eng.txt -lines | p -lang=LangEng | l | wf -file=examples.eng2ger.new
Form Ger to Eng:
From Ger to Eng: see examples.txt and object-order.gfs
example.txt contains german example sentences marked "positive", "negative", "dubious",
some with two marks. The marks may not always be convincing, as some orderings of negation
and quantified nps afford particular intonation and meaning. (Also, there are incorrect
parse trees due to misuse of MassNP etc., so it needs some inspection to see if the content
of examples.*.out is as it ought to be.)
(Some of these examples need german/TestLangGer|Eng)
Part of examples.txt needs TestLangGer|Eng for parsing and translation, in particular
those with reflexive ternary verbs or quaternary verbs (which are not in the RGL).
From Eng to Ger:
examples.eng.txt could also be parsed using LangEng instead of TestLangEng|Ger.
Lang> rf -file=examples.eng.txt -lines | p -lang=LangEng | l -lang="Eng,Ger" -treebank | wf -file=examples.eng.new
Lang> rf -file=examples.eng.txt -lines | p -lang=LangEng | l -lang="Eng,Ger" | wf -file=examples.eng2ger.new
Using give_V3 is confusing, as both objects are connected with noPrep. The examples are
repeated using send_V3, which attaches its indirect object with toPrep.
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